Shared Decision Making for Syncope in the Emergency Department: A Randomized Controlled Feasibility Trial
Bibliographic record
Abstract
OBJECTIVES: Significant practice variation is seen in the management of syncope in the emergency department (ED). We sought to evaluate the feasibility of performing a randomized controlled trial of a shared decision making (SDM) tool for low-to-intermediate-risk syncope patients presenting to the ED. METHODS: We performed a randomized controlled trial of adults (≥30 years) with unexplained syncope who presented to an academic ED in the United States. Patients with a serious diagnosis identified in the ED were excluded. Patients were randomized, 1:1, to receive either usual care or a personalized syncope decision aid (SynDA) meant to facilitate SDM. Our primary outcome was feasibility, i.e., ability to enroll 50 patients in 24 months. Secondary outcomes included patient knowledge, involvement (measured with OPTION-5), rating of care, and clinical outcomes at 30 days post-ED visit. RESULTS: After screening 351 patients, we enrolled 50 participants with unexplained syncope from January 2017 to January 2019. The most common reason for exclusion was lack of clinical equipoise to justify SDM (n = 124). Patients in the SynDA arm tended to have greater patient involvement, as shown by higher OPTION-5 scores: 52/100 versus 27/100 (between-group difference = -25.4, 95% confidence interval = -13.5 to -37.3). Both groups had similar levels of clinical knowledge, ratings of care, and serious clinical outcomes at 30 days. CONCLUSIONS: Among ED patients with unexplained syncope, a randomized controlled trial of a shared decision-making tool is feasible. Although this study was not powered to detect differences in clinical outcomes, it demonstrates feasibility, while providing key lessons and effect sizes that could inform the design of future SDM trials.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".